A Micro Inertial Measurement unit (μIMU) which is based on Micro-Electro-Mechanical Systems (MEMS) accelerometers and gyroscope sensors is developed for real-time recognition of human hand motion. By using appropriate filtering, transformation and sensor fusion algorithms, a ubiquitous digital writing instrument is produced for recording handwriting on any surface. In this paper, we propose a m...

The Kalman filter cannot be used with nonstationary state space models. To circumvent this difficulty, a conditional state space model and a new algorithm, calIed the conditional Kalman filter, can be used. The conditional state space model is obtained by first selecting adequately that part oof the initial state vector which has an unspecified distribution and then conditioning on O. Using the...

Semiautogenous milling is difficult to control both because of its non-linear behavior and the effects of overloading due to increases in the ore charge or variations in ore characteristics. Advanced control strategies and operational change detection methods are thus in need of strengthening using techniques such as state estimation. Non-linear state estimation is a complex task for which vari...

Particle filters are an alternative to approximate the Kalman filter for nonlinear problems. This paper intends to assess the potential of Particle Filter (PF) and its variants in the context of the state estimation problem of a three phase induction motor. The conventional Particle Filter (SIR-PF), and particle filters that employ importance sampling through proposal distributions such as Part...

SOC Estimation Gregory L. Plett, consultant to Compact Power Inc., and Assistant Professor, University of Colorado at Colorado Springs Abstract hHEV environment harsh: Rates up to ±25C, very dynamic rate profiles. hVery different from low-rate / constant-rate portable electronics. hSOC estimation must be done differently — if precise SOC estimation is required by the HEV, then a very accurate c...

Although many applications of small Autonomous Surface Vessels rely on two-dimensional state estimation, inspection tasks based on long-range sensors require more accurate attitude estimates. In the context of shoreline monitoring relying on a nodding laser scanner, we evaluate three different extended Kalman filter approaches with respect to an accurate ground truth in the range of millimeters...

In this paper, a range difference estimation technique with NLOS error mitigation by using biased Kalman filter for ultra-wideband (UWB) environments is presented. NLOS error is considered one of the major error sources in wireless location systems. To improve TDOA location accuracy in UWB location systems, NLOS identification and mitigation techniques suitable for UWB systems are derived. Kalm...

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Rece...

A standard approach to tracking is to use the Extended Kalman Filter (EKF) applied to a non-linear state-space model. We will compare two conceivable choices of state variables for modeling civil aircrafts. One where Cartesian velocities are used and one where absolute velocity and heading angle are used. In both choices, Cartesian coordinates are used for position and angular velocity for turn...

SLAM (Simultaneous Localization and Mapping) is a fundamental problem when an autonomous mobile robot explores an unknown environment by constructing/updating the environment map and localizing itself in this built map. The all-important problem of SLAM is revisited in this paper and a solution based on Adaptive Unscented Kalman Filter (AUKF) is presented. We will explain the detailed algorithm...